Statistik - Descriptive Statistics
Details
| ID | 2858618 |
| Duration | 3.0 days |
| Methods | Lecture with examples and exercises. |
| Prerequisites | General knowledge of math |
| Target group | Data Analysts |
Overview
Descriptive statistics is the discipline of quantitatively describing the main features of a collection of data, or the quantitative description itself. Descriptive statistics are distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent. Univariate analysis involves describing the distribution of a single variable, including its central tendency (including the mean, median, and mode) and dispersion (including the range and quantiles of the data-set, and measures of spread such as the variance and standard deviation). The shape of the distribution may also be described via indices such as skewness and kurtosis. Characteristics of a variable's distribution may also be depicted in graphical or tabular format, including histograms and stem-and-leaf display. When a sample consists of more than one variable, descriptive statistics may be used to describe the relationship between pairs of variables. In this case, descriptive statistics include quantitative measures of dependence. This training covers all the fundamentals of descriptive statistics which can be used in marketing, controlling and engineering. You will learn theory and the mathematical foundations in lectures with examples and you will train your new knowledge in practical hands-on labs and exercices.\n
Dates
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Your benefits at a glance
- Flexible preferred date
- Customized content
- Intensive exchange
- High practical relevance
Comelio Media
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Services
- Lunch / catering
- Help with hotel / travel
- Comelio certificate
- Flexible: free cancellation up to one day before
Content
Introduction to Statistics
Descriptive and Inductive Statistics - Uni-/Bi- and Multi-variate Statistics - Summary tables: Grouped data, Frequency distributions, Contingency tables - Statistical graphics: Bar chart, Biplot, Box plot, HistogramUnivariate Analysis: Measures of Central Tendency
Mean (Arithmetic, Geometric, Harmonic) - Median - ModeUnivariate Analysis: Measures of Dispersion
Range - Variance and Standard deviation - Coefficient of variation - Percentiles - Interquartile range - Shape: Variance, Skewness, Kurtosis, MomentsUnivariate Analysis: Measures of Shape
Skewness - Kurtosis - MomentsBivariate Analysis: Dependence
Continuous data: Pearson product-moment correlation, Partial correlation, Scatter plot - Ordinal data: Rank correlation (Spearman's rho, Kendall's tau) - Categorical data: Contingency tables, Cramer´s V, Phi coefficient, Chi coefficientBivariate Analysis: Regression
Linear regression: Simple linear regression, Ordinary least squares - Regression analysis: Errors and residuals, Regression model validation, Estimations - Overview of non-linear regression modelsInstructor
Marco Skulschus (born in Germany in 1978) studied economics in Wuppertal (Germany) and Paris (France) and wrote his master´s thesis about semantic data modeling. He started working as a lecturer and consultant in 2002.Publications
- Grundlagen empirische Sozialforschung (Comelio Medien)
978-3-939701-23-1 - System und Systematik von Fragebögen (Comelio Medien)
978-3-939701-26-2 - Oracle PL/SQL (Comelio Medien)
978-3-939701-40-8 - MS SQL Server - T-SQL Programmierung und Abfragen (Comelio Medien)
978-3-939701-69-9